STRUCTURAL MODIFICATION OF THE HUFFMAN METHOD FOR COMPRESSION OF DENSE DATA STREAMS WITHOUT LOSS ON A RCS

The paper considers the problem of determining the current coordinates of moving object in theconditions of unstable signal from the global navigation satellite system (GNSS). The relevance of thework is due to the fact that in recent years moving object are increasingly used in virtually all sectors ofindustry, agriculture, transportation, solving a variety of tasks of surveillance, reconnaissance, monitoringthe state of controlled objects, search and rescue operations, cargo delivery and much more. At the sametime, the success of flight missions largely depends on how accurately and efficiently its onboard navigationsystem works in real time. The existing solutions for creating onboard positioning systems involve theuse of inertial and GNSS. However, they have the disadvantage of partial or complete absence of datafrom the GNSS (Global Positioning System). This paper describes a method for maintaining a given accuracyof moving object spatial positioning under conditions of partial or complete absence of data from theobject's GSP. This approach is based on a combination of computer vision methods for processing videostream frames from the moving object on-board vision system (OVS) in order to ensure positioning accuracyunder conditions of partial or complete absence of data from satellite navigation systems. Based onthe advanced method, an algorithm has been developed for automated determination of moving objectcoordinates in the absence of georeferencing data from global positioning systems (GPS). Experimentshave been carried out, which demonstrated the reduction of time costs for description and matching of keypoints and improvement of the accuracy of image matching. The developed algorithm was used to solvethe problem of satellite image matching, which is an important step in the moving object positioning problemwithout the use of global geo-referencing data.